My previous posts for Raphael’s blog have focussed on critiquing poor methodology and over-enthusiastic data interpretation when it comes to imaging the surface structure of functionalised nanoparticles. This time round, however, I’m in the much happier position of being able to highlight an example of good practice in resolving (sub-)molecular structure where the authors have carefully and systematically used scanning probe microscopy (SPM), alongside image recognition techniques, to determine the molecular termination of Ag nanoparticles.

For those unfamiliar with SPM, the concept underpinning the operation of the technique is relatively straight-forward. (The experimental implementation rather less so…) Unlike a conventional microscope, there are no lenses, no mirrors, indeed, no optics of any sort [1]. Instead, an atomically or molecularly sharp probe is scanned back and forth across a sample surface (which is preferably atomically flat), interacting with the atoms and molecules below. The probe-sample interaction can arise from the formation of a chemical bond between the atom terminating the probe and its counterpart on the sample surface, or an electrostatic or magnetic force, or dispersion (van der Waals) forces, or, as in scanning tunnelling microscopy (STM), the quantum mechanical tunnelling of electrons. Or, as is generally the case, a combination of a variety of those interactions. (And that’s certainly not an exhaustive list.)

Here’s an example of an STM in action, filmed in our lab at Nottingham for Brady Haran’s Sixty Symbols channel a few years back…

Scanning probe microscopy is my first love in research. The technique’s ability to image and manipulate matter at the single atom/molecule level (and now with individual chemical bond precision) is seen by many as representing the ‘genesis’ of nanoscience and nanotechnology back in the early eighties. But with all of that power to probe the nanoscopic, molecular, and quantum regimes come tremendous pitfalls. It is very easy to acquire artefact-ridden images that look convincing to a scientist with little or no SPM experience but that instead arise from a number of common failings in setting up the instrument, from noise sources, or from a hasty or poorly informed choice of imaging parameters. What’s worse is that even relatively seasoned SPM practitioners (including yours truly) can often be fooled. With SPM, it can look like a duck, waddle like a duck, and quack like a duck. But it can too often be a goose…

That’s why I was delighted when Raphael forwarded me a link to “Real-space imaging with pattern recognition of a ligand-protected Ag374 nanocluster at sub-molecular resolution”, a paper published a few months ago by Qin Zhou and colleagues at Xiamen University (China), the Chinese Academy of Science, Dalian (China), the University of Jyväskylä (Finland), and the Southern University of Science and Technology, Guandong (China). The authors have convincingly imaged the structure of the layer of thiol molecules (specifically, tert-butyl benzene thiol) terminating 5 nm diameter silver nanoparticles.

What distinguishes this work from the stripy nanoparticle oeuvre that has been discussed and dissected at length here at Raphael’s blog (and elsewhere) is the degree of care taken by the authors and, importantly, their focus on image reproducibility. Instead of using offline zooms to “post hoc” select individual particles for analysis (a significant issue with the ‘stripy’ nanoparticle work), Zhou et al. have zoomed in on individual particles in real time and have made certain that the features they see are stable and reproducible from image to image. The images below are taken from the supplementary information for their paper and shows the same nanoparticle imaged four times over, with negligible changes in the sub-particle structure from image to image.

This is SPM 101. Actually, it’s Experimental Science 101. If features are not repeatable — or, worse, disappear when a number of consecutive images/spectra are averaged – then we should not make inflated claims (or, indeed, any claims at all) on the basis of a single measurement. Moreover, the data are free of the type of feedback artefacts that plagued the ‘classic’ stripy nanoparticle images and Zhou et al. have worked hard to ensure that the influence of the tip was kept to a minimum.

Given the complexity of the tip-sample interactions, however, I don’t quite share the authors’ confidence in the Tersoff-Hamann approach they use for STM image simulation [2]. I’m also not entirely convinced by their comparison with images of isolated molecular adsorption on single crystal (i.e. planar) gold surfaces because of exactly the convolution effects they point towards elsewhere in their paper. But these are relatively minor points. The imaging and associated analysis are carried out to a very high standard, and their (sub)molecular resolution images are compelling.

A-C above are STM data, while D-F are constant height atomic force microscope images [3], of thiol-passivated nanoparticles (synthesised by Nicolas Goubet of Pileni’s group) and acquired at 78 K. (Zhou et al. similarly acquired data at 77K but they also went down to liquid helium temperatures). Note that while we could acquire sub-nanoparticle resolution in D-F (which is a sequence of images where the tip height is systematically lowered), the images lacked the impressive reproducibility achieved by Zhou et al. In fact, we found that even though we were ostensibly in scanning tunnelling microscopy mode for images such as those shown in A-C (and thus, supposedly, not in direct contact with the nanoparticle), the tip was actually penetrating into the terminating molecular layer, as revealed by force-distance spectroscopy in atomic force microscopy mode.

The other exciting aspect of Zhou et al.’s paper is that they use pattern recognition to ‘cross-correlate’ experimental and simulated data. There’s increasingly an exciting overlap between computer science and scanning probe microscopy in the area of image classification/recognition and Zhou and co-workers have helped nudge nanoscience a little more in this direction. Here at Nottingham we’re particularly keen on the machine learning/AI-scanning probe interface, as discussed in a recent Computerphile video…

Given the number of posts over the years at Raphael’s blog regarding a lack of rigour in scanning probe work, I am pleased, and very grateful, to have been invited to write this post to redress the balance just a little. SPM, when applied correctly, is an exceptionally powerful technique. It’s a cornerstone of nanoscience, and the only tool we have that allows both real space imaging and controlled modification right down to the single chemical bond limit. But every tool has its limitations. And the tool shouldn’t be held responsible if it’s misapplied…

[1] Unless we’re talking about scanning near field optical microscopy (SNOM). That’s a whole new universe of experimental pain…

[2] This is the “zeroth” order approach to simulating STM images from a calculated density of states. It’s a good starting point (and for complicated systems like a thiol-terminated Ag374 particle probably also the end point due to computational resource limitations) but it is certainly a major approximation.

[3] Technically, dynamic force microscopy using a qPlus sensor. See this Sixty Symbols video for more information about this technique.

Our Topical Review on the characterization of gold nanoparticles (GNPs) has just been published in the Bionconjugate Chemistry Special Issue “Interfacing Inorganic Nanoparticles with Biology”.

The literature is abounding in works on GNPs for applications in biology, catalysis and sensing, among others. GNPs’ appeal resides in their optical properties, together with the well-developed methods of synthesis available and the possibility of functionalizing their surface with small molecules of interest, which can readily self-assemble on the GNPs’ surface forming a monolayer.

However, allegedly the structure and organization of self-assembled monolayers (SAMs) at the GNPs’ surface are in fact aspects too often neglected [though surely not on this blog; RL]. Such elucidation is challenging experimentally, but it is crucial not only to ensure reproducibility, but also to design nanosystems with defined (bio)physicochemical and structural properties, which could then be envisioned to assemble in more complex systems from a “bottom-up” approach.

Our Topical Review gives an overview of the current knowledge and methods available to characterize the GNPs’ surface with different molecular details.

Cartoon illustrating the different levels of GNPs’ surface characterization discussed in the Topical Review.

First, the experimental methods commonly used to provide the basic characterization of functionalized GNPs, such as identification and quantification of the ligands within the monolayer, are detailed with the aid of some examples.

Second, the experimental methods providing information on the monolayer thickness and compactness are reviewed.

Third, considering that the SAM’s thickness and compactness do not only depend on the amount of ligands within the monolayer, but also on their conformation, the experimental methods that can provide such insights are recapitulated. However, we also stressed on the limitations intrinsic to these methods and on the challenges associated to the determination of the structure of SAMs on GNPs.

Fourth, we summarized some of the approaches used to give insights into the organization of different ligands within a SAM. Indeed, mixed SAMs on GNPs are useful since they can impart to the nanoparticles different functionalities and offer a way to tune their stability.

Fifth, highlighting again the limited insights into the SAM’s structure and organization that can be gathered with experimental techniques, we detailed some examples where a combination of experimental and computational approaches was able to provide a compelling description of the system and to assess molecular details that could not have been revealed experimentally.

Overall, this Topical Review gives emphasis on the importance of GNPs’ surface characterization and on fact that even though a number of experimental techniques are available, they are intrinsically limited and they cannot provide a fully detailed picture. Hence, it is advantageous to combine experimental and theoretical approaches to design nanoparticles with desired (bio)physicochemical properties [such as, e.g., our paper under review, currently available as a preprint; RL].

Lauren K. Wolf has written a nice overview of the stripy nanoparticle controversy for Chemical & Engineering News, the weekly magazine published by the American Chemical Society. It starts like this:

AS TRUTH SEEKERS, scientists often challenge one another’s work and debate over the details. At the first-ever international scientific conference, for instance, leading chemists argued vociferously over how to define a molecule’s formula. A lot of very smart people at the meeting, held in Germany in 1860, insisted that water was
OH, while others fought for H 2 O.

That squabble might seem tame compared with a dispute that’s been raging
in the nanoscience community during the past decade. […]

Read it allhere… if you have access. If you don’t, email me and I will send you a pdf.

That is the title of Bogart et al Nano Focus article published yesterday in ACS Nano.

Abstract:

Nanoparticles have the potential to contribute to new modalities in molecular imaging and sensing as well as in therapeutic interventions. In this Nano Focus article, we identify some of the current challenges and knowledge gaps that need to be confronted to accelerate the developments of various applications. Using specific examples, we journey from the characterization of these complex hybrid nanomaterials; continue with surface design and (bio)physicochemical properties, their fate in biological media and cells, and their potential for cancer treatment; and finally reflect on the role of animal models to predict their behavior in humans.

The first discussions about this paper took place during the European Materials Research Society meeting in Strasbourg last year (where several of the authors co-chaired symposium Q).

In his latest Materials Views column entitled “Nanochemistry Reproducibility”, Geoffrey Ozin offers a strongly worded and rather devastating view of scientific standards in nanoscience and makes recommendation for future improvements. Read it all here.

His concluding “Nano Food for Thought” is as follows:

On a final note in the context of nano reproducibility, how does the nano community judge scientific quality? Some might say that the work with amazing images and routine science is looked upon more favorably than the work with amazing science and routine images. High quality images cannot be a substitute for high quality science. It should be science first and photography second! The question is, how representative are these art nano images of your pet nanomaterial and the reproducibility of the synthesis. […]

Geoffrey Ozin does not give any particular example. To my knowledge, he has not expressed any judgement regarding the stripy nanoparticle articles.

Abstract — Protein cages can be engineered to tailor its function as carriers for therapeutic and diagnostic agents. They are formed by self-assembly of multiple subunits forming hollow spherical cage structures of nanometer size. Due to their proteinaceous nature, the protein cages allow facile modifications on its internal and external surfaces, as well as the subunit interfaces. Modifications on the internal and the external surfaces allow conjugation of small molecule drugs or contrast agent and targeting ligands, respectively. The subunit interaction is of special interest in engineering controlled release property onto the protein cage. Two protein cages, E2 protein and ferritin, are described.

Biodata

Sierin Lim obtained both her B.S. and Ph.D. degrees from University of California, Los Angeles (UCLA) in Chemical Engineering and Biomedical Engineering, respectively. She joined Nanyang Technological University (NTU) as Assistant Professor at the end of July 2007 after a 2.5-year postdoctoral research at University of California, Irvine (UCI). She was the Singapore recipient of the 2012 Asia Pacific Research Networking Fellowship from the International Federation for Medical and Biological Engineering.

Dr. Lim’s research focuses on the design, engineering, and development of hybrid nano/microscale devices from biological parts by utilizing protein engineering as a tool. In particular, she is interested in self-assembling protein-derived nanocapsules and photosynthetic biological materials. The project scopes range from understanding the self-assembly mechanism of the nanocapsules and engineering theranostic carriers to the improvement of electron transfer efficiency in a photosynthetic electrochemical cell.